A genetic algorithm for chance constrained programming

This paper presents a genetic algorithm for chance constrained goal programming, chance constrained multiobjective programming. In order to deal with stochastic constraints, Monte Carlo simulation is employed to check the feasibility of a solution in the proposed genetic algorithm. Finally, the authors use some numerical examples to illustrate the effectiveness of genetic algorithms for chance constrained programming.